Mobiusi/Durian-Plantation-Epiphyte-Moss-Image-Dataset

Durian Plantation Epiphyte Moss Image Dataset

Current durian plantations face the challenge of identifying epiphytic moss, which affects plant health and yield. Existing solutions often rely on manual monitoring, which is time-consuming, labor-intensive, and lacks accuracy. This dataset aims to improve the detection efficiency and accuracy of epiphytic moss through automated image recognition technology. Data collection was carried out using drones and high-definition cameras in various environments and weather conditions, ensuring adequate daylight for optimal image quality. In terms of quality control, the data underwent multiple rounds of annotation, combined with reviews by agricultural experts to ensure accuracy and consistency. The annotation team consisted of more than 20 experts in botany and image processing. Data preprocessing included image cropping, noise filtering, and color correction, with storage organized in JPG format. The dataset is organized in a structured folder format for convenient retrieval and usage. The dataset maintains a high level of annotation accuracy with a 96% recognition rate. In terms of consistency and completeness, it has undergone multiple verifications to ensure reliable data quality. In technological innovation, multi-angle shooting and AI enhancement algorithms were introduced to improve recognition performance under various lighting conditions. This dataset helps enhance durian plantation management efficiency. Compared to other datasets on the market, this dataset is more targeted and practical, especially in terms of coverage and diversity for different growth stages. It achieved over a 20% improvement in moss recognition accuracy. The dataset design makes it suitable for current agricultural research and can be applied to other plant moss identification tasks, offering a high level of versatility.

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
moss_species	string	Refers to the type of moss appearing in the image.
density_level	string	Describes the density level of moss in the image.
moss_color	string	Records the dominant color tone of moss in the image.
growth_stage	string	Identifies the growth stage of moss in the image.
plant_interaction	string	Explains the interaction between moss and other plants.
image_clarity	string	Evaluates the image clarity for accurate moss identification.
light_exposure	string	Describes the lighting conditions in the image.

Compliance Statement

Authorization Type	CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com